Editorial. Facets of data literacy: Advancing the field through interdisciplinary lenses

Main Article Content

Davide Taibi
Juliana Elisa Raffaghelli
Manuel León-Urrutia


Digital data has consolidated as the fuel of technological development. The commercialisation of Large Language Models and Generative Artificial Intelligence has led to the massive adoption of Artificial Intelligence applications by the general public, bringing data literacy to a prominent position in the public debate. In this data-driven economy and society, academia and industry have to collaborate to meet the needs of a data-literate workforce (León et. al., 2020).  Moreover, data literacy is also a powerful enabler of civic engagement, as it empowers individuals and communities to keep governments transparent and accountable, tackle local issues, and navigate their own data ecosystems. In this regard, it is also essential support for the wide exploitation of open data and open government resources. Nonetheless, the data-driven practices have led to critical situations, injustice, and concern in several areas of human activity, from the public to the private sector.

The growing availability of data and the increasing incentives to use it, in fact, have brought about a rising concern known as data literacy. This concern is strongly driven by the fact that many individuals lack the necessary skills to effectively utilise the available data, as well as the necessary competencies to make ethical and responsible use of such data. This special issue contains papers supporting this notion, emphasising that data literacy encompasses not only the ability to work with data but also the ability to understand its use and value within different contexts, including areas like citizen science and digital civic engagement.

While there has been an increase in research on data literacy in recent years, much of the existing research is confined to specific disciplinary areas such as research data, and there is still a relative neglect of the civic and citizen context (Yousef, Walker, & León-Urrutia, 2021). Simultaneously, data has increasingly become a part of citizens' lives through the presence of algorithms, machine learning, and the potential for artificial intelligence. Hence, this special issue has aimed to gather papers that explore the possibilities of comprehensive multidisciplinary research on the societal implications of data literacy, its significance, and how it can be effectively fostered.

In fact, the concept of data literacy, as the educational activity aimed at developing understanding and skills relating to such dimensions of our societies, spots the contextual and diversified nature of data practices in response to or reaction to metrics, quantification, and algorithms. The research on the topic has highlighted the existence of practices of participation linked to data appropriation to express cultural diversity, civic empowerment, and hence social and economic innovation. Instead, another strand of research is particularly focused on uncovering algorithmic bias, unstructured data usage, and the search for data justice. From these diversified strands of research, there emerges a clear need to embrace interdisciplinary discussion and collaboration in order to explore and expand the concept and practice of data literacy. Specifically, teachers and educators at all levels of the schooling system, including higher education and lifelong learning, are called to transform their practice through the introduction of data literacy as a contextualised and complex perspective on an emerging technological revolution in contemporary society.

To this aim, the focus of this special issue was to gather research that deals with data literacy as an emerging topic, and an area of knowledge and practice that requires reflection, discussion and transformative action. To that end, we highlight the relevance of building understanding on the basis of empirical research as a perspective on a complex and emerging social problem. Specifically, we called for contributions referring to research dealing with conceptual competence frameworks or models, applying constructs, and/or catering to practical cases showing the benefits of different data literacy experiences for different target groups across lifelong learning.

We collected four relevant research articles, which bring to the fore the polysemy embedded in the concept of data literacy, as well as the multiplicity of practices it can generate.

Data literacy is not a crucial competence only in Higher education contexts, it is more and more important to promote the introduction of these competences at an earlier stage

Article Details



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Yousef, A. M. F., Walker, J. C., & León-Urrutia, M. (2021). Defining data literacy communities by their objectives: A text mining analysis. In Companion Publication of the 13th ACM Web Science Conference 2021 (WebSci ‘21 Companion). Association for Computing Machinery, New York, NY, USA, 26–33. https://doi.org/10.1145/3462741.3466663
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